Job Description
We are looking for a visionary Generative AI Engineer to join our elite team in San Francisco. Our mission is to architect the next generation of autonomous AI agents that will define the 2026 technology landscape. You will work at the forefront of Large Language Model (LLM) evolution, focusing on fine-tuning, retrieval-augmented generation (RAG), and multi-modal reasoning.
In this high-impact role, you will not just use existing models—you will build the infrastructure for the future.
Responsibilities
- Architect & Train Models: Design and train large-scale transformer architectures from scratch or fine-tune state-of-the-art open-source models (Llama 3, Mistral) for specific enterprise use cases.
- Optimize Inference: Engineer high-performance inference pipelines to reduce latency and cost while maximizing output quality for real-time applications.
- Build Agentic Workflows: Develop autonomous agents capable of complex reasoning, tool use, and long-horizon planning.
- Security & Compliance: Implement robust data governance and safety guardrails to prevent hallucinations and ensure regulatory compliance.
- Collaborate: Partner with product managers and data scientists to translate business requirements into cutting-edge AI solutions.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Machine Learning, or a related field (or equivalent practical experience).
- Experience: 5+ years of experience in software engineering with a focus on Deep Learning or Natural Language Processing.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow. Deep understanding of Hugging Face Transformers, LangChain, and vector databases (Pinecone, Weaviate).
- Tooling: Experience with MLOps tools (Docker, Kubernetes, MLflow) and cloud platforms (AWS, GCP, or Azure).
- Problem Solving: Demonstrated ability to tackle complex algorithmic challenges and optimize performance bottlenecks.